Pretreatment ADC Histogram Analysis as a Prognostic Imaging Biomarker for Patients with Recurrent Glioblastoma Treated with Bevacizumab: A Systematic Review and Meta-analysis

BACKGROUND: The mean ADC value of the lower Gaussian curve (ADC(L)) derived from the bi-Gaussian curve-fitting histogram analysis has been reported as a predictive/prognostic imaging biomarker in patients with recurrent glioblastoma treated with bevacizumab; however, its systematic summary has been lacking. PURPOSE: We applied a systematic review and meta-analysis to investigate the predictive/prognostic performance of ADC(L) in patients with recurrent glioblastoma treated with bevacizumab. DATA SOURCES: We performed a literature search using PubMed, Scopus, and EMBASE. STUDY SELECTION: A total of 1344 abstracts were screened, of which 83 articles were considered potentially relevant. Data were finally extracted from 6 studies including 578 patients. DATA ANALYSIS: Forest plots were generated to illustrate the hazard ratios of overall survival and progression-free survival. The heterogeneity across the studies was assessed using the Cochrane Q test and I-2 values. DATA SYNTHESIS: The pooled hazard ratios for overall survival and progression-free survival in patients with an ADC(L) lower than the cutoff values were 1.89 (95% CI, 1.53?2.31) and 1.98 (95% CI, 1.54?2.55) with low heterogeneity among the studies. Subgroup analysis of the bevacizumab-free cohort showed a pooled hazard ratio for overall survival of 1.20 (95% CI, 1.08?1.34) with low heterogeneity. LIMITATIONS: The conclusions are limited by the difference in the definition of recurrence among the included studies. CONCLUSIONS: This systematic review with meta-analysis supports the prognostic value of ADC(L) in patients with recurrent glioblastoma treated with bevacizumab, with a low ADC(L) demonstrating decreased overall survival and progression-free survival. On the other hand, the predictive role of ADC(L) for bevacizumab treatment was not confirmed.